Librarian Bot: Add base_model information to model

This pull request aims to enrich the metadata of your model by adding [`braindao/flan-t5-cnn`](https://huggingface.co/braindao/flan-t5-cnn) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.

How did we find this information? We extracted this infromation from the `adapter_config.json` file of your model.

**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.

For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien).

If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!

README.md

@@ -1,32 +1,29 @@
 ---
-license: mit
-library_name: peft
-datasets:
-- samsum
 language:
 - en
+license: mit
+library_name: peft
 tags:
 - summarization
 - text-generation
 - toxicity-reduction
 - reinforcement-learning
+datasets:
+- samsum
 widget:
-- text: >-
-    Summarize the following Conversation: Kate: Good morning. Kai: Hi! How
-    official! Kate: I wrote it at 4am Kai: I've noticed. Why? Kate: I had to get
-    up early to catch the bus to the airport Kai: Where are you flying? Kate: To
-    Antwerp! I'm fed up with Cambridge Kai: poor thing. Why? Kate: Just a
-    stupid, elitist place without a soul. Or with a soul made of money. Kai: Try
-    to rest a bit in Belgium, do not work too much. Kate: I have to work, but at
-    least not in this soulless place. Kai: When are you coming back? Kate: I
-    have to see my supervisor on Monday <unk> Kai: not too long a break Kate:
-    Still better than nothing. Summary:
+- text: 'Summarize the following Conversation: Kate: Good morning. Kai: Hi! How official!
+    Kate: I wrote it at 4am Kai: I''ve noticed. Why? Kate: I had to get up early to
+    catch the bus to the airport Kai: Where are you flying? Kate: To Antwerp! I''m
+    fed up with Cambridge Kai: poor thing. Why? Kate: Just a stupid, elitist place
+    without a soul. Or with a soul made of money. Kai: Try to rest a bit in Belgium,
+    do not work too much. Kate: I have to work, but at least not in this soulless
+    place. Kai: When are you coming back? Kate: I have to see my supervisor on Monday
+    <unk> Kai: not too long a break Kate: Still better than nothing. Summary:'
   example_title: Summarization Example 1
-- text: >-
-    Summarize the following Conversation: Dean: I feel sick Scott: hungover?
-    Dean: no, like I ate something bad Scott: what did you eat yesterday? Dean:
-    breakfast at Coffee Lovers' Scott: this is a rather safe place Dean: and
-    Chinese from TaoTao for dinner Scott: now we have a suspect Summary:
+- text: 'Summarize the following Conversation: Dean: I feel sick Scott: hungover?
+    Dean: no, like I ate something bad Scott: what did you eat yesterday? Dean: breakfast
+    at Coffee Lovers'' Scott: this is a rather safe place Dean: and Chinese from TaoTao
+    for dinner Scott: now we have a suspect Summary:'
   example_title: Summarization Example 2
 pipeline_tag: text2text-generation
 inference:
@@ -39,6 +36,7 @@ inference:
     no_repeat_ngram_size: 2
     num_return_sequences: 1
     do_sample: true
+base_model: braindao/flan-t5-cnn
 ---
 
 # Flan-T5 (base-sized) Dialogue Summarization with reduced toxicity using RLAIF